VisionLab Events
HIGHLIGHT
OTHER NEWS
ReViT: Enhancing vision transformers with residual attention
Vision Transformer (ViT) self-attention mechanism is characterized by feature collapse in deeper layers, resulting in the vanishing of low-level visual features. However, such features can
2 Settembre 2024 Nessun commento
S-GEAR: Semantically Guided Representation Learning for Action Anticipation (ECCV2024)
Action anticipation is forecasting future activity from a partially observed sequence of events. However, this task is exposed to intrinsic future uncertainty and the difficulty
2 Settembre 2024 Nessun commento
23 Agosto 2024 Nessun commento
23 Agosto 2024 Nessun commento
23 Agosto 2024 Nessun commento
23 Agosto 2024 Nessun commento
Computer Vision Conferences
Nvidia News
- Tuning Flash Attention for Peak Performance in NVIDIA CUDA Tile
- How to Minimize Game Runtime Inference Costs with Coding Agents
- cuTile.jl Brings NVIDIA CUDA Tile-Based Programming to Julia
- Building Telco Reasoning Models for Autonomous Networks with NVIDIA NeMo
- 5 New Digital Twin Products Developers Can Use to Build 6G Networks
- Develop Native Multimodal Agents with Qwen3.5 VLM Using NVIDIA GPU-Accelerated Endpoints
- Maximizing GPU Utilization with NVIDIA Run:ai and NVIDIA NIM
- Making Softmax More Efficient with NVIDIA Blackwell Ultra
- Using NVFP4 Low-Precision Model Training for Higher Throughput Without Losing Accuracy
- Accelerating Data Processing with NVIDIA Multi-Instance GPU and NUMA Node Localization
- Unlock Massive Token Throughput with GPU Fractioning in NVIDIA Run:ai
- Topping the GPU MODE Kernel Leaderboard with NVIDIA cuda.compute
- How NVIDIA Extreme Hardware-Software Co-Design Delivered a Large Inference Boost for Sarvam AI’s Sovereign Models
- Build AI-Ready Knowledge Systems Using 5 Essential Multimodal RAG Capabilities
- R²D²: Scaling Multimodal Robot Learning with NVIDIA Isaac Lab
Microsoft News
- Phi-4-reasoning-vision and the lessons of training a multimodal reasoning model
- Trailer: The Shape of Things to Come
- CORPGEN advances AI agents for real work
- Media Authenticity Methods in Practice: Capabilities, Limitations, and Directions
- Project Silica’s advances in glass storage technology
- Rethinking imitation learning with Predictive Inverse Dynamics Models
- Paza: Introducing automatic speech recognition benchmarks and models for low resource languages
- UniRG: Scaling medical imaging report generation with multimodal reinforcement learning
- Multimodal reinforcement learning with agentic verifier for AI agents
- OptiMind: A small language model with optimization expertise
- Agent Lightning: Adding reinforcement learning to AI agents without code rewrites
- Promptions helps make AI prompting more precise with dynamic UI controls
- GigaTIME: Scaling tumor microenvironment modeling using virtual population generated by multimodal AI
- Reducing Privacy leaks in AI: Two approaches to contextual integrity
- Fara-7B: An Efficient Agentic Model for Computer Use
Google AI News
- Generative AI to quantify uncertainty in weather forecasting
- AutoBNN: Probabilistic time series forecasting with compositional bayesian neural networks
- Computer-aided diagnosis for lung cancer screening
- Using AI to expand global access to reliable flood forecasts
- ScreenAI: A visual language model for UI and visually-situated language understanding
- SCIN: A new resource for representative dermatology images
- MELON: Reconstructing 3D objects from images with unknown poses
- HEAL: A framework for health equity assessment of machine learning performance
- Cappy: Outperforming and boosting large multi-task language models with a small scorer
- Talk like a graph: Encoding graphs for large language models
- Chain-of-table: Evolving tables in the reasoning chain for table understanding
- Health-specific embedding tools for dermatology and pathology
- Social learning: Collaborative learning with large language models
- Croissant: a metadata format for ML-ready datasets
- Google at APS 2024